
\begin{table}
\begin{center}
\begin{tabular}{l D{)}{)}{9)2} D{)}{)}{9)0} D{)}{)}{9)2} D{)}{)}{9)0} D{)}{)}{9)0}}
\toprule
 & \multicolumn{1}{c}{Care} & \multicolumn{1}{c}{Fairness} & \multicolumn{1}{c}{Loyalty} & \multicolumn{1}{c}{Authority} & \multicolumn{1}{c}{Sanctity} \\
\midrule
GAL-TAN (CHES)           & 0.08 \; (0.16)       & 0.25 \; (0.17)  & 0.26 \; (0.15)      & 0.16 \; (0.17)  & 0.04 \; (0.17)  \\
Year                     & -0.08 \; (0.15)      & -0.18 \; (0.16) & -0.16 \; (0.14)     & -0.26 \; (0.16) & -0.15 \; (0.17) \\
Government Participation & -0.94 \; (0.29)^{**} & -0.19 \; (0.31) & 0.75 \; (0.27)^{**} & 0.39 \; (0.30)  & -0.45 \; (0.35) \\
\midrule
AIC                      & 104.74               & 108.63          & 104.52              & 108.11          & 113.08          \\
BIC                      & 114.07               & 117.97          & 113.85              & 117.44          & 122.41          \\
Log Likelihood           & -46.37               & -48.32          & -46.26              & -48.05          & -50.54          \\
Num. manifestos          & 35                   & 35              & 35                  & 35              & 35              \\
Num. groups: countries   & 4                    & 4               & 4                   & 4               & 4               \\
Var: Country (Intercept) & 0.43                 & 0.26            & 1.70                & 0.48            & 0.00            \\
Var: Residual            & 0.68                 & 0.80            & 0.60                & 0.76            & 1.01            \\
\bottomrule
\multicolumn{6}{l}{\scriptsize{$^{***}p<0.001$; $^{**}p<0.01$; $^{*}p<0.05$}}
\end{tabular}
\caption{Regression table for all manifestos in German, scored with CCR (multi ref/embed) for the dimension Virtue.}
\label{tab:app_reg_de_ccr_multi_to_multi_virtue}
\end{center}
\end{table}
